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The i2b2 Temporal Data-Mining Solution for Automated Reconstruction of Different Breast Cancer Patterns of Care over a Decade of Observation

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Open Access
Article Type Research Article
Subject General Science
OCLC JBRES Record
Alberto Zambelli, Flavia Jacobs*, Arianna Ghirardi, Lorenzo Chiudinelli, Mauro Bucalo, Nicola Barbarini, Sara Du2019Alessandro3, Arianna Masciulli, Vittoria Fotia, Riccardo Bellazzi and Carlo Tondini
Issue: Volume5-Issue6
Pages: 630-639
Received: 2024-06-14
Accepted: 2024-06-21
Published: 2024-06-21

Abstract

Background: In oncology, Patterns of Care (PoC) provide a detailed overview of all cancer-treatment interventions and recapitulate the entire patient’s journey. While manual-chart PoC reviewing is time-consuming, the use of Electronic Health Records (EHRs) enables the creation of data-mining solutions to automatically reconstruct the whole cancer trajectory with different granularity.

Methods: We tested the ability of the i2b2 (Informatics for Integrating Biology and Bedside) solution to support the automatic reconstruction of the PoC for consecutive and unselected HER2+ and TNBC breast cancer patients through a retrospective EHRs analysis over a decade of observations.

Results: From 2008 to 2017, 561 HER2+ and 412 TNBC patients were retrospectively identified by i2b2 platform at the Papa Giovanni XXIII Hospital in Bergamo. Most patients, 74.3% in the HER2 group and 71.8% in the TNBC group, received a (neo) adjuvant chemotherapy, with anti-HER2 drugs whenever indicated. Among the HER2 cohort, the 5-year Time to Treatment Change (TTC) and Overall Survival (OS) were 69.4% and 77.4% respectively, with 25% of patients receiving up to 3 lines of treatment in metastatic setting. Among the TNBC cohort, the 5-year TTC and OS were 59.3% and 69.4% respectively, with only 2% of patients receiving active treatment as third line of therapy. The consistency of the automated PoC reconstruction had to be reviewed in 1/3 of cases to clean conflicting data.

Conclusion: The i2b2 solution has the potential to provide a retrospective, automated reconstruction of the different PoC, with limited manual-chart review refinement and might contribute to support investigations in the field of real-world data.

FullText HTML FullText PDF DOI: 10.37871/jbres1935 Crossmark

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Copyright

© 2024 Zambelli A, et al. Distributed under Creative Commons CC-BY 4.0 Creative CommonsAttribution

How to cite this article

Zambelli A, Jacobs F, Ghirardi A, Chiudinelli L, Bucalo M, Barbarini N, D’Alessandro S, Masciulli A, Fotia V, Bellazzi R, Tondini C. The i2b2 Temporal Data-Mining Solution for Automated Reconstruction of Different Breast Cancer Patterns of Care over a Decade of Observation. J Biomed Res Environ Sci. 2024 Jun 21; 5(6): 630-639. doi: 10.37871/jbres1935, Article ID: JBRES1935, Available at: https://www.jelsciences.com/articles/jbres1935.pdf

Subject area(s)

Computer Science

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